Background Social media has become an indispensable tool in the face of natural disasters due to its broad appeal and ability to quickly disseminate information. For instance, Twitter is an important source for disaster responders to search for (1) topics that have been identified as being of particular interest over time, i.e., common topics such as...

The explosive and viral nature of social media creates massive amounts of high-dimensional data. Features such as hashtags, keywords, or slang words are created every day and quickly become popular within a short period of time. However, social media data is not fully structured and its features are usually not predefined. One way to resolve this problem...

Background Attributed networks are networks whose nodes contain rich sets of features or attributes. In social networks, for instance, attributes may be user interests, while for paper citation networks they may be papers associated with an institution or scholar. The pervasiveness of attributed networks across numerous domains has given rise to the...

Background Tremendous volumes of sequential event data continue to be generated across diverse technological domains. Whether they be “retweets” sprouting across the social media network Twitter, stock trades, or ride-share vehicle usage patterns, effective data processing of past occurrences can improve near-term predictability of future...